the same but still different: forms in e-government · the same but still different: forms in...
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The Same but Still Different: Forms in E-Government
Hendrik Scholta
University of Muenster – ERCIS, Muenster, Germany
Abstract Forms are essential artifacts of government service
delivery to transmit information between the customer
and the government. However, customers perceive
forms as too complex. Since the complexity of a system
is influenced by the diversity of its components, this
paper’s main contribution is the identification of
characteristics of forms and their components that
drive the diversity of different forms. For this purpose,
we evaluate a set of 69 forms of 27 German
municipalities according to various criteria. The
results reveal that different partitions of forms in
subparts, varying sets of presented and requested data,
different element types and varying captions for equal
elements drive the complexity of current government
forms. On the contrary, orders of elements are similar
across the forms at hand.
1. Introduction
Forms are important artifacts in the course of
government service delivery [6]. A form is an interface
between the government and the customer to exchange
information and collect relevant data [25]. Therefore,
forms are main carriers of information [17] and input
of government services [28] since they initiate a
government service and contain the necessary data to
deliver the service. Forms are views on data [31] since
they prepare data to present it to external stakeholders.
However, although they are crucial for government
service delivery, forms are still perceived as too
complex by customers and have negative influence on
the customers’ satisfaction. In Germany, 56% of the
citizens complain about a low usability of e-
government services [14]. Although 60% of German
citizens take the opinion that forms are relevant for
their satisfaction with government services, the citizens
are not satisfied with the comprehensibility of forms
[9]. In the United States, citizens desire simpler e-
government services and complain that too much
information is requested from them [1].
Despite a reasonable amount of research on forms
in general and in the course of e-government services
in particular, an analysis of current government forms’
degree of complexity and the complexity’s influencing
factors is missing in literature.
The complexity of a system is influenced by the
diversity of its components and their relations [24]. In
this paper, we focus on the diversity of the forms’
components in the course of government service
delivery. We investigate what characteristics of the
forms’ components drive the diversity of current
forms. Forms have an inherent complexity that is
defined by the regulations, laws and involved
organizations of a service and cannot be eliminated.
Besides, there is a high number of design guidelines to
decrease complexity and increase user convenience of
forms. Due to these two reasons, we do not aim at
reducing the complexity of an individual form based
on its underlying regulations and design guidelines.
Instead, the systems at hand consist of a collection of
forms of different municipalities for the same
government service. Thus, we focus on the complexity
that is driven by the diversity of different forms and
their components.
Consequently, this paper answers the following
research question: To what extent do current forms for
the same government service in different German
municipalities have a diverse structure (RQ1)?
According to RQ1, we focus on the forms’ structure
and exclude the graphical arrangement of components
from consideration. We answer the research question
by analyzing the diversity of 69 current government
forms according to a set of criteria. Thereby, we
answer the following question: What characteristics of
current government forms and their components drive
their diversity (RQ2)? The answer of RQ2 helps to
understand what initiatives should focus on when
harmonizing forms.
The remainder of this paper is structured as
follows: In section 2, we present related work of our
research. Subsequently, section 3 explains our research
design. In section 4, we provide the results of our
study. Section 5 discusses the results. Finally, we
conclude and give an outlook on future work in
section 6.
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Proceedings of the 50th Hawaii International Conference on System Sciences | 2017
URI: http://hdl.handle.net/10125/41465ISBN: 978-0-9981331-0-2CC-BY-NC-ND
2. Research Background
2.1. Form Representations and Structures
“A form is an information holding object” [27, p.
500] and a context-specific view on data stored in a
database [31,36]. In literature, there is a comprehensive
amount of work specifying different levels of
granularity on and components of forms
[22,27,30,34,35,36].
Analogously to [22,27], we distinguish between
abstract forms, display forms and form instances.
Abstract forms are models that abstract from concrete
graphical design of forms but represent a form’s fields
and their order on the form, e.g. the field “Country”
follows the field “State”. An abstract form can be
specialized by different display forms specifying
design parameters, e.g. the creation of a HTML form
for a government service with the specification of the
field “Country” as drop-down menu. A form instance
is an electronic or paper-based form that is filled with
values for a certain case, e.g. the value “USA” is
provided for the field “Country”. The remainder of this
paper will deal with display forms and their
representation as abstract forms.
In addition to its name as heading, a form has a
body with fields and groups [22]. To avoid ambiguity,
we will refer to these groups as field groups in the
following. Fields represent attributes of data entities
and can be used to input and update data or present and
output data [36]. A field can be further described with
properties such as its caption, position on the form,
data type such as integer, date or string, and the length
of the field. Depending on the way fields are presented,
the authors in [26] distinguish between tuple forms and
relation forms. A tuple form consists of fields with
captions for each data entity whereas in a relation form
the data entities are displayed in a compressed table
format. Recent research on web forms distinguishes
different types of fields [4,33]: Text box, radio buttons,
drop-down menu, list box and checkbox.
Whereas fields are the smallest units on a form,
field groups are used to structure fields according to
different subjects on the same level of abstraction (e.g.
a differentiation between the field groups “name” and
“address”) or on the same subject but different levels
of abstraction (e.g. the field group “applicant” consists
of the field group “address”). Therefore, field groups
are composites of fields and/or subordinate field
groups [22].
2.2. Forms in Action
Before customers use forms in the course of e-
government services, they are developed by
governments. For this purpose, many guidelines for the
design of web forms can be applied [3,5,15,33]. The
guidelines include design requirements considering the
needs of increasingly aging users [21,23] or
approaches to improve the accessibility of government
forms for handicapped people [19]. Despite this
research on designs of forms, their complexity is still
an open issue. In order to cope with the remaining
complexity, mechanisms such as automatic filling [32]
and automatic completion [8] can support the customer
during the completion of a form.
Diversity of components can be reduced through
standardization if a standard is developed and
implemented. “In the simplest sense, a standard is an
agreed-upon way of doing something.” [29, p. 1]
Standardization in e-government is often discussed in
terms of interoperability [12,13,16,18]. Since
interoperability allows IT systems to exchange
information, it describes an alternative interface to
forms between governments and citizens and
companies. Therefore, frameworks such as XÖV [7]
are standards for interfaces between governments and
customers and can serve as basis for the
standardization of forms.
In addition to interoperability as first step for the
standardization of forms, first dedicated concepts for
this goal have been proposed. In [10], the authors
present a role concept and process to standardize and
manage forms in governments. In [2], a concept for the
development of standardized information on services,
processes and forms is introduced. However, these
concepts are still to be implemented in practice.
3. Research Design
To investigate the diversity of forms in German
municipalities, we applied a four-step approach that is
visualized in figure 1: (1) Identification of suitable
services and their initiating forms that are to be
investigated, (2) Construction of comparable and
abstract representations of the forms, (3) Development
of groups consisting of elements with similar topics
and functions across the forms and (4) Analysis of the
diversity within the groups. The subjects of
consideration are the municipalities of the 20 greatest
German cities regarding population. Since there are
federal states without a city that belongs to the 20
greatest cities, we additionally considered the capitals
of those federal states. In total, we analyzed 27
municipalities.
In the course of step (1), we made a list of services
for which most of the municipalities provide a
reasonable amount of initiating forms on their
websites. To apply a common understanding of what a
service is, we used the terminology suggested by the
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LeiKa [11]. It is a standardized service catalogue for
German governments that is managed by a government
institution. Based on the list of potential services with a
high amount of forms, we selected three services as
target for our investigation. Our selection was guided
by the following requirements: (a) The municipalities
have to offer a high amount of forms for these services
and (b) the main legal foundation for each selected
service is defined on a different federal level. The
result of this step is a set of application forms of 27
German municipalities for the initiation of three
services. There can be more than one form per
municipality if a municipality offers a PDF form and a
web form.
Figure 1. Research Design
In step (2), we developed abstract constructs for a
uniform representation of the forms’ structures and
created a sequential abstract form for each display
form. As forms differ in their graphical design, we had
to map their display elements to standardized abstract
elements to make the forms comparable and
analyzable. For this purpose, we started deductively
with abstract element types suggested in literature. To
cover relevant differences of display elements, we
refined the set of abstract element types inductively by
applying the set iteratively to represent the display
forms of step (1). After the last iteration, we used the
final set of abstract element types to create abstract
forms for the display forms at hand for succeeding
processing. A single researcher created the final
abstract forms to ensure consistency of the
representations. The result of this step is twofold. First,
a set of abstract element types that is used to represent
the display forms abstracting from display details.
Second, we transformed each display form to a
sequential abstract form representing the form’s
display elements from the top to the bottom and from
the left to the right.
Subsequently in step (3), we built groups of
abstract elements for each service that have similar
semantics, i.e. deal with the same topic and have the
same function. We refer to these groups as semantic
groups in the following. The topic indicates the real-
world entity that is described by the abstract element
whereas the function differentiates between abstract
elements that present or capture information. We
aimed at developing semantic groups with a disjoint
meaning. In some cases, we had to assign an abstract
element to more than one semantic group. For the
forms of the first service, we inductively formed
semantic groups by merging abstract elements or
existing semantic groups based on the abstract
elements’ captions. We reused the first service’s set of
semantic groups during the creation of the semantic
groups for the subsequent two services. We assigned
the abstract elements to these groups and inductively
created new semantic groups if necessary. The results
of this step are semantic groups of abstract elements
across all abstract forms of each service.
During step (4), the similarity of the abstract
elements of each semantic group was analyzed to
evaluate the diversity of the entire forms. If forms are
homogenous, the abstract elements in the semantic
groups do not only have similar semantics but also
similar representative properties such as captions and
positions. Based on characteristics of forms and
knowledge gained during the previous steps, we
developed a set of criteria and their computations to
analyze the diversity. Then, we applied the criteria to
the abstract forms of each service and their semantic
groups. The result of this step is twofold: First, a set of
criteria and potential drivers to evaluate the diversity of
the abstract forms. Second, values for the criteria that
indicate the diversity of each service’s forms.
4. Results
4.1. Step (1): Services
In the course of step (1), we selected the following
three services: A) Dog license fee registration, B) Issue
31 Forms for
Service A
27 Municipalities
Forms for
Service B
Forms for
Service C
2
Literature on Form Representations and Structures
Development of
Comparable
Representations
1. a
2. b
2.1. c
3. d
4. e
1. b
1.1. c
2. f
2.1 g
2.2 h
3. e
Semantic Group 1
Semantic Group 2
a b b cc
de f gh e
4
Criteria for Degree of Diversity
Semantic Group 1 Semantic Group 2
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of a certificate of eligibility for public housing and C)
Registration at the residents’ registration office.
The dog license fee is a municipal tax on dog
keeping. It is collected annually for each dog. The legal
foundations are municipal statutes and therefore
defined on the third federal level. The municipalities
are not forced to collect this tax. However, each of the
municipalities at hand provides a registration form for
the dog license fee. Two of the municipalities offer a
PDF form and a web form. In total, there are 29 forms
for the first service.
A certificate of eligibility for public housing
confirms that a tenant is allowed to rent an
accommodation in the course of subsidized housing.
The applicants have to fulfil criteria such as upper
limits for incomes that vary depending on the federal
state. This is due to legal foundations that are defined
on the second federal layer. Laws from the first federal
layer only apply if federal states have not passed an
own law. 21 of the municipalities at hand provide an
application form for the second service.
Whenever a citizen moves to another city, a
registration at the residents’ registration office is
obligatory. The same applies to citizens that obtain a
residence in Germany for the first time. The legal
foundations are specified on the first federal level.
However, they can be extended on the second and third
federal level. In total, 19 of the municipalities at hand
offer a registration form on their websites.
4.2. Step (2): Abstract Forms
Table 1 presents the basic set of abstract element
types that belongs to the first result of step (2) and was
used to create abstract forms for the subsequent
analyses. The abstract element types are categorized
according to five categories. Category 1 contains
abstract element types to represent different kinds of
field groups: Tuple field group for tuple forms, Column
group and Row group for relation forms.
The categories 2, 3 and 4 provide abstract element
types for fields. Since fields are used to present data
(e.g. the address of the municipality where the
completed form has to be sent to) and capture data (e.g.
the address of the applicant), we divide fields into
output (category 2) and input (categories 3 and 4)
fields. In addition to form headings, we observed form
subheadings on the forms at hand. Labels present texts
to users and graphics provide graphical illustrations
such as logos.
Whereas category 3 covers abstract element types
for different kinds of input fields on tuple forms,
category 4 is dedicated to relation forms. In addition to
the abstract element types suggested in literature, we
added the abstract element type Cloze to category 3.
Similarly to Text box, it allows users to enter free text.
However, the captions are structured differently. In the
case of a Cloze the input of the user is integrated into
the caption whereas a Text box is separated from its
caption, e.g. by a colon.
In category 4, a Table consists of Rows and
Columns.
Table 1. Atomic abstract element types
Name Explanation/Example
Category 1: Field groups
Tuple field
group
Column
group
Row group
Category 2: Output fields
Form
heading Heading of a form
Form
subheading Subheading of a form
Label A label presents text
Graphic For instance, a logo of a municipality
Category 3: Input fields on tuple forms
Text box
Cloze
List box
List box item
Drop-down
menu
Drop-down
menu item
Checkbox
Radio button
Category 4: Input fields on relation forms
Table
Column
Row
Category 5: Supplementary abstract element type
Help text
Abstract elements of the previously mentioned
types can be enriched with supplementary information
Text box:
A cloze is part of a sentence.
Tuple field group:
Column Column
Row
Row
...
...
...
...
Table:
Row
group
Column group
Text box:
A cloze is part of a sentence.
List box item
List box item
List box item
List box item
List box:
Drop-down menu:Drop-down menu item
Drop-down menu item
Checkbox
Radio button
Column Column
Row
Row
...
...
...
...
Table:
Text box:(Help text)
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specified in category 5. This category comprises the
abstract element type Help text that enriches fields with
information on what data has to be entered in which
way.
The abstract element types from the field-related
categories 2, 3 and 4 can be combined with abstract
element types from all categories to composed abstract
element types. The introduction of composed abstract
element types is necessary to be able to represent the
diversity of structural constructs that occur on the
forms at hand and combine parts of fields, field groups
and supplementary elements. Table 2 provides an
excerpt of these types. In total, we identified 22
composed abstract element types on the forms at hand1.
Table 2. Excerpt of composed abstract element types
Name Example
Text box
with help
text
Checkbox
with
cloze Checkbox
with tuple
field
group
The second result of step (2) is a set of abstract
forms that are comparable representations of the forms’
contents. To construct abstract forms, the display
elements were mapped to according abstract elements
of the types mentioned above. An exemplary display
form excerpt and its abstract form equivalent are
presented in figure 2 and table 3. The excerpt
comprises a single tuple field group. This tuple field
group consists of eight elements, which is indicated by
indents (2nd structural layer). The gender of the dog is
indicated by two checkboxes that are located on the 3rd
structural layer and grouped by a tuple field group.
1 Composed abstract element types in addition to table 2: Text box
with graphic, Text box with tuple field group, Text box with tuple field group and help text, Column with tuple field group, Row with
text box, Row with tuple field group, Table with cloze, Cloze with
help text, Cloze with tuple field group, Checkbox with help text, Checkbox with text box, Checkbox with text box and tuple field
group, Checkbox with text box and help text, Checkbox with cloze
and help text, Checkbox with cloze and tuple field group, Form heading with tuple field group, Form heading with checkbox and
tuple field group, Form heading with checkbox and text box and help
text, Radio button with help text.
Figure 2. Exemplary display form excerpt
Table 3. The excerpt’s representation as abstract form
1st layer 2nd layer 3rd
layer Type
Information
regarding
the dog
Tuple field
group
Breed Text box
Involved breeds
(if mixed-breed
dog)
Text box
Dog’s name Text box
Color Text box
Date of birth Text box
Gender Tuple field
group male Checkbox
female Checkbox
Special
characteristic or
chip number
Text box
How long have
you been keeping
the dog in [city]?
Text box
4.3. Step (3): Semantic Groups
In step (3), we created groups of abstract elements
that have similar semantics. Due to consistency
reasons, the semantic groups only contain abstract
elements that occur on the first structural layer of the
abstract forms. We identified generic semantic groups
such as “Applicant” where the customer enters
personal information. These groups are relevant to all
three services. On the contrary, specific semantic
groups such as “Landlord/Lessor” are dedicated to one
specific service. Due to space limitations, we only
consider generic semantic groups in the following.
Table 4 presents the generic semantic groups as results
of step (3). As stated in chapter 3, we describe each
group by a topic and function.
The dog is being kept in your
household in [city] since:
(Day / Month / Year)
I moved from
at with the dog.
acquired
Previous owner surname, given name
Address
Date of birth Gender
male female
Special characteristic or chip number
How long have you been keeping the dog in [city]?
Dog’s name
Breed Involved breeds (if mixed-breed dog)
Color
Information regarding the dog
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Table 4. Generic semantic groups
No. Topic Function Explanation
1 Administrative
procedure Present
Information regarding the procedure, e.g. upcoming steps, explanations of legal
specifications and guidelines
2 Applicant Capture General information regarding the applicant, e.g. the name, address and date of birth
3 Authentication Capture The applicant’s signature and additional information such as the signature’s date
4 Case processing Capture Fields that are filled by the authority after the applicant has submitted the form, e.g.
internal notes
5 Completeness and
correctness Present
Declaration that the applicant confirms the correctness and completeness of the
submitted information
6 Delivered documents Capture The applicant indicates which documents are enclosed to the form
7 Form’s driving object Capture The central object of the application or registration: The dog (service A), the
applicant (service B), the residence (service C)
8 Form filling Present Advices and guidelines on how to fill the form, e.g. a specification of the symbol
that indicates mandatory fields
9 Form heading Present This group comprises the headings of the forms
10 Form subheading Present This group contains the forms’ subheadings
11 Identification number Capture The applicants may need to enter numbers that allow an identification, e.g. a tax
number
12 Miscellaneous Both This semantic group comprises all abstract elements that cannot be assigned to
another group, i.e. have a different semantic than other abstract elements
13 Necessary documents Present Specification what proofs and certificates have to be enclosed to the form
14 Privacy Present Information on privacy regulations, e.g. legal foundations for data transfers to third
parties
15 Public authority Present General information of the form issuing institution, e.g. its address and opening
hours
16 Supplementary notes Capture The applicant can enter additional free text to submit further remarks
4.4. Step (4): Diversity of Forms
To evaluate the diversity of forms, we derived
criteria that are introduced in table 5.
Table 5. Criteria for diversity of forms
Criterion I: Number of Forms
Indicates how many forms are provided by the
municipalities for a service and how many forms provide at
least one abstract element that belongs to a certain semantic
group. If the value for this criterion is low, then only a
limited number of municipalities provides a form or certain
content on the first structural layer.
Criterion II: Average Number of Elements
Determines the average number of abstract elements that an
entire form or a part that belongs to a certain semantic
group has on the first structural layer. If the values are high,
then the forms have many abstract elements on the first
structural layer.
Criterion III: Dispersion of Number of Elements
Calculates the standard deviation of the number of abstract
elements on the first structural layer. If the values are high,
then the forms follow different ways of partitioning forms
since some use field groups to structure fields whereas
others state fields directly on the first structural layer.
Criterion IV: Number of Different Element Types
Computes the number of different abstract element types on
the first structural layer of entire forms and semantic groups
with function “Capture”. Semantic groups with function
“Present” are excluded since there is essentially one type
for output fields (label). If the values for this criterion are
high, then the forms use different types to capture similar
content.
Criterion V: Number of Different Captions
Determines how many different captions exist for the
abstract elements of a semantic group on the first structural
layer. This number is divided by the number of abstract
elements on the first structural layer to obtain the relative
number of different captions per abstract element in the
semantic group.
All semantic groups that contain long labels are excluded
from the application of this criterion since texts can hardly
be identical.
If the values are close to 1, then every abstract element has
a different caption and similar content is described
differently on the forms at hand.
Criterion VI: Variety of Captured Data
Analyzes the forms’ highest structural layers that request
data from the applicant, i.e. contain input fields. Regarding
the excerpt visualized in table 3, the second structural layer
is analyzed since the first layer only contains a field group
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that structures the input fields of the second layer.
The criterion analyzes the equality of the data that is
requested. For this purpose, we grouped similar abstract
elements of the analyzed layers analogously to step (3) of
the research design. The returned values indicate how many
abstract elements belong to a group of one, two, three etc. If
many abstract elements belong to small groups, then the
requested data is different.
When applying this criterion, we considered semantic
groups that capture information from the applicant and
contain more than one abstract element per form. Analyses
of sets are not meaningful if single elements are compared.
Criterion VI.1 returns the number of abstract elements in
groups with ten or less elements. Criterion VI.2 indicates
the number of abstract elements that belong to a group with
more than ten elements. Hence, if the value for VI.1 is low
and the value for VI.2 is high, then equal data is requested.
Criterion VII: Variety of Orders
To evaluate the similarity of orders of fields that capture
data and belong to a certain semantic group, we compare
the orders of the abstract elements of one form to the order
of abstract elements of a reference form. The reference
form is the form that provides the most abstract elements
for the semantic group. This criterion returns the average
value of the pairwise comparisons.
Similarly to the Levenshtein distance [20] for strings, we
compare orders by counting the minimal number of
insertions, deletions and substitutions to transform one list
of abstract elements to the list of the reference form. To
exclusively focus on orders, we only take equal elements in
both lists into account.
Since this criterion focuses on abstract elements that
capture data from the applicant, it considers the same
semantic groups and operates on the same structural layers
as criterion VI.
A high value is returned, if the orders of the forms’
elements for a certain semantic group highly differ to the
order of the reference form.
We applied the criteria to the forms at hand and the
semantic groups (SG). The evaluation results are
presented in tables 6 and 7. The semantic groups are
stated in the rows, whereas the criteria are mentioned
in the columns. The values for the criteria are given for
each of the services A, B and C.
According to the values for criterion I, the semantic
group “Applicant” occurs on every form. Other
frequent semantic groups are “Form’s driving object”
and “Form heading”. However, there are semantic
groups such as “Privacy” and “Form filling” that are
only covered by some of the forms. The majority of the
semantic groups appears on less than 50% of the
forms.
Table 6. Application of the criteria – Part I
Crit. I II III IV
Serv.
SG A B C A B C A B C A B C
Form 29 21 19 15.72 21.81 17.84 5.81 12.02 3.55 19 15 12
1 16 10 13 1.44 1.4 1.46 0.73 0.7 0.52 - - -
2 29 21 19 2.48 1.48 2.63 1.94 0.98 1.12 7 4 4
3 24 14 18 1.79 2.5 1.94 0.88 1.22 0.87 2 3 1
4 16 14 16 2.19 5.14 1.69 1.72 9.55 0.48 3 7 2
5 9 15 0 1 1 0 0 0 0 - - -
6 4 3 0 1 1 0 0 0 0 1 1 0
7 27 Cf. SG 2 19 2.29 Cf. SG 2 1.68 1.84 Cf. SG 2 1.29 10 Cf. SG 2 6
8 12 7 4 1 1.29 1.25 0 0.76 0.5 - - -
9 28 21 18 1 1.1 1 0 0.3 0 - - -
10 4 2 0 1.25 1 0 0.5 0 0 - - -
11 9 1 1 1.11 1 1 0.33 0 0 2 1 1
12 13 17 10 1.38 2 1.5 0.51 1.06 0.97 - - -
13 2 7 0 1 1 0 0 0 0 - - -
14 13 8 5 1.23 1.38 1.4 0.44 0.52 0.55 - - -
15 25 17 3 2.04 2.35 1.67 1.27 1.27 1.15 - - -
16 3 2 0 1 1 0 0 0 0 2 2 0
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Table 7. Application of the criteria – Part II
Crit. V VI.1 VI.2 VII
Serv. SG
A B C A B C A B C A B C
2 0.89 0.9 0.24 99 157 135 171 70 363 0.1 0.15 0.13
3 0.6 0.71 0.51 28 36 35 17 0 0 0.83 0 0
7 0.68 Cf. SG 2 0.41 187 Cf. SG 2 52 73 Cf. SG 2 61 0.51 Cf. SG 2 0.22
9 0.54 0.83 0.28 - - - - - - - - -
10 0.8 1 0 - - - - - - - - -
11 0.88* 0* 0* - - - - - - - - -
16 1 1 0 - - - - - - - - -
*: The semantic group “Identification number” subsumes different numbers (A: 5, B: 1, C: 1). We applied criterion V to each single number that
occurs more than once and state the average of these values for each service in the table. The value 0 indicates the nonexistence of a number
which occurs more than once.
The criteria II and III indicate that the standard
deviations for the number of elements on the first
structural layer are high in relation to the averages for
the majority of semantic groups and entire forms. For
example, the standard deviation of “Applicant” (1.94)
for service A is 78% of the average (2.48). Similarly,
the standard deviation of the entire forms for service
B is 12.02 and reaches 55% of the average (21.81). In
contrast, for some semantic groups such as
“Completeness and correctness” of service B the
standard deviation is 0.
The values for criterion IV provide insights on the
number of different element types. The semantic
groups “Form’s driving object” and “Applicant” are
the groups with the most different element types. The
majority of the semantic groups incorporates three or
less different element types. However, the entire
forms use 12, 15 or 19 different abstract element
types on the first structural layer. Dividing the
number of element types by the number of forms
reveals that more than every other form introduces a
new abstract element type.
Regarding the services A and B, the values for
criterion V are close to 1. When excluding semantic
group 11 from consideration due to the different
calculation, the lowest value for service A is 0.54 and
the lower bound for service B is 0.71. On the
contrary, the values for service C are low with a
maximum value of 0.51.
The values for criterion VI are not unambiguous.
The majority of the abstract elements of the semantic
group “Authentication” does not have many
equivalents on other forms (e.g. 36 > 0). On the
contrary, the other two semantic groups “Applicant”
and “Form’s driving object” have cases where many
equivalent abstract elements exist (e.g. 135 < 363)
and cases where the majority does not have many
equivalents (e.g. 187 > 73).
Considering criterion VII, all values approximate
0 with two exceptions: One value is around 0.5 and
one value is close to 1. In consequence, the majority
of values for criterion VII is low.
5. Discussion
Our results reveal that current forms in German
municipalities have certain commonalities. However,
there is a high diversity in their structure that results
in complexity and can be addressed by harmonization
initiatives. Table 8 contains a detailed discussion of
the results and the diversity’s driving factors.
Table 8. Discussion of the results
Different Number of Partitions (Criteria II and III)
The main form characteristic that drives complexity is the
partition with different structural levels (criteria II and
III). According to our results the standard deviations for
the number of elements on the first layer are high in most
cases. The standard deviation is low for labels since they
present texts to users and do not require other elements.
Consequently, the forms are partitioned differently.
Different Sets of Presented and Captured Data (Criteria I
and VI)
According to criterion I, the contents on the first structural
layer highly differ. Thus, the data that is presented to or
captured from the customer is highly different across the
forms. On the one hand, this may be obvious since the
forms have different partitions as indicated by criteria II
and III. If different partitions are used, then the data that is
requested on the first structural on one form may be
captured on the second layer of another form. Hence, the
contents may be hidden by the structural layers and not
discovered by criterion I. On the other hand, criterion VI
indicates that despite certain commonalities there is
potential for harmonization regarding the set of data that
is captured by fields.
Different Element Types (Criterion IV)
According to the results for the semantic groups regarding
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criterion IV, in most cases the number of different
element types is low in relation to the number of forms
and the number of element types (41). However,
considering the entire forms reveals that many different
element types are used on the forms’ first structural layer.
Different Captions (Criterion V)
Another characteristic that is relevant for the forms’
diversity are different captions of elements. Although
different elements should have different captions and the
forms have many different elements as shown above, the
values for criterion V are too close to 1 since the elements
have similar semantics. Thus, there is potential to
harmonize captions.
Different Orders (Criterion VII)
The results for criterion VII indicate that the average
distances to the according reference forms are small with
regard to orders. Consequently, criterion VII is not that
relevant for harmonization initiatives at the moment since
it indicates a low diversity. If the contents of current
forms are similar, then also their orders are similar.
Taking everything into account, the absence of
similar partitions, similar sets of presented and
captured data, similar element types and equal
captions for equal elements drives the diversity of
current government forms. Orders are not a big issue
at the moment. Most relevant are similar partitions.
Initiatives should harmonize granularities and take
into account the forms’ modularity by providing
harmonized building blocks that can be reused for
different forms and services.
When harmonizing forms, initiatives should
consider federal levels and their different legal
foundations. Some differences in the forms’
structures are defined by legal foundations.
Consequently, the potential for harmonization is
limited by legal foundations. However, there are
cases such as the business registration in Germany
where the legislator provides a template that can be
used to create individual forms and thereby supports
harmonization.
6. Conclusion and Outlook
In this paper, we analyzed to what extent current
forms in German municipalities have a diverse
structure. Additionally, we identified characteristics
of current forms and their components that drive
diversity. For the first time, we showed that form
diversity is an important issue. Especially different
partitions of forms should be targeted in the future.
This paper makes three contributions to research:
First, the current list of abstract elements to represent
display forms’ structures can be applied for further
analyses. Second, the generic semantic groups
comprise contents that forms in general should
contain and can be integrated into design guidelines.
Third, the criteria to evaluate forms’ diversity can be
applied and extended in future research.
Additionally, we make two contributions to
practice. First, we emphasized the need for form
harmonization. Second, we identified characteristics
of forms that should be focused by initiatives when
harmonizing forms.
Despite its contributions, this paper is subject to
limitations and potential for future work. First, we
only considered the generic semantic groups and
excluded the specific semantic groups from the paper.
Although an integration of these semantic groups
reveals a more comprehensive view on the diversity
of forms, the open issues for harmonization remain
the same. Second, since the selection of the reference
form influences the values for criterion VII, more
sophisticated calculations can be developed for this
criterion in the future. Third, a similarity measure for
forms may be constructed by integrating and
weighting the criteria into one figure. Fourth, in this
paper we developed criteria that are applied to
individual services. In the future, further criteria for
inter-service comparisons can be developed and
calculated.
We raised the need for a harmonization of forms.
It is the task of researchers to conceptualize and
support initiatives that are dedicated to this issue with
their method and domain knowledge.
Acknowledgment
I would like to thank Annika Verhorst for her
support during the creation of this paper.
References [1] Accenture. Digital Government: Your Digital Citizens
are Ready, Willing… and Waiting. 2015.
https://www.accenture.com/t20151014T210834__w__/us-
en/_acnmedia/Accenture/Conversion-
Assets/DotCom/Documents/Global/PDF/Dualpub_16/Acce
nture-Your-Digital-Citizens-Ready-Willing-Waiting-2.pdf
[Accessed: 03-Mar-2016].
[2] Ahrend, N., Wolf, P., Räckers, M., Dentschev, A., and
Jurisch, M. Federal Information Management – Context
and Effects. Proceedings of the 44. Jahrestagung der
Gesellschaft für Informatik, Stuttgart, (2014), 1499–1511.
[3] Axelsson, K. and Ventura, S. Reaching Communication
Quality in Public E-Forms – A Communicative Perspective
on E-Form Design. Proceedings of the 6th International
Conference on Electronic Government, Regensburg,
(2007), 342–353.
[4] Bargas-Avila, J.A., Brenzikofer, O., Roth, S.P., Tuch,
A.N., Orsini, S., and Opwis, K. Simple but Crucial User
Interfaces in the World Wide Web: Introducing 20
Guidelines for Usable Web Form Design. In R. Mátrai, ed.,
2567
User Interfaces. InTech, 2010, 1–10.
[5] Bargas-Avila, J.A., Oberholzer, G., Schmutz, P., de
Vito, M., and Opwis, K. Usable error message presentation
in the World Wide Web: Do not show errors right away.
Interacting with Computers 19, 3 (2007), 330–341.
[6] Becker, J., Algermissen, L., and Falk, T. Modernizing
Processes in Public Administrations: Process Management
in the Age of e-Government and New Public Management.
Springer-Verlag, Berlin, Heidelberg, 2012.
[7] Büttner, F., Bartels, U., Hamann, L., et al. Model-driven
standardization of public authority data interchange.
Science of Computer Programming 89, (2014), 162–175.
[8] Chaudhuri, S. and Kaushik, R. Extending
Autocompletion To Tolerate Errors. Proceedings of the
ACM SIGMOD International Conference on Management
of Data, Providence, (2009), 707–718.
[9] Federal Statistical Office. Zufriedenheit der
Bürgerinnen und Bürger in Deutschland mit behördlichen
Dienstleistungen: Ausgewählte Ergebnisse der
Zufriedenheitsbefragung 2015. 2015. https://www.amtlich-
einfach.de/SharedDocs/Downloads/Ergebnisse_Buerger.pd
f?__blob=publicationFile&v=3 [Accessed: 16-Feb-2016].
[10] Folmer, E., Matzner, M., Räckers, M., Scholta, H., and
Becker, J. Standardized but Flexible Information Exchange
for Networked Public Administrations – A Method.
Transforming Government: People, Process and Policy 10,
2 (2016).
[11] Geschäfts- und Koordinierungsstelle LeiKa. LeiKa.
2015. http://leika.zfinder.de [Accessed: 16-Oct-2015].
[12] Gottschalk, P. Maturity levels for interoperability in
digital government. Government Information Quarterly 26,
1 (2009), 75–81.
[13] Guijarro, L. Interoperability frameworks and
enterprise architectures in e-government initiatives in
Europe and the United States. Government Information
Quarterly 24, 1 (2007), 89–101.
[14] Initiative D21 and ipima. eGovernment Monitor 2015.
2015. http://www.egovernment-monitor.de/die-
studie/2015.html [Accessed: 01-Dec-2015].
[15] Jarrett, C. and Gaffney, G. Forms that Work:
Designing Web Forms for Usability. Morgan Kaufmann,
Burlington, 2009.
[16] Klischewski, R. and Scholl, H.J. Information quality as
a common ground for key players in e-government
integration and interoperability. Proceedings of the 39th
Hawaii International Conference on System Sciences,
Kauai, (2006), 1–10.
[17] Klischewski, R. Ontologies for e-document
management in public administration. Business Process
Management Journal 12, 1 (2006), 34–47.
[18] Kubicek, H. and Cimander, R. Three dimensions of
organizational interoperability: Insights from recent studies
for improving interoperability frame-works. European
Journal of ePractice 6, (2009), 3–14.
[19] Kuhn, N., Richter, S., Schmidt, M., and Truar, A.
Improving Accessibility to Governmental Forms.
Proceedings of the 1st TC 13 Human-Computer Interaction
Symposium, Milano, (2008), 119–128.
[20] Levenshtein, V.I. Binary Codes Capable of Correcting
Deletions, Insertions and Reversals. Soviet physics-doklady
10, 8 (1966), 707–710.
[21] Lines, L., Ikechi, O., and Hone, K.S. Accessing e-
Government Services: Design Requirements for the Older
User. Proceedings of the 4th International Conference on
Universal Access in Human-Computer Interaction, Beijing,
(2007), 932–940.
[22] Lum, V.Y., Choy, D.M., and Shu, N.C. OPAS: An
office procedure automation system. IBM Systems Journal
21, 3 (1982), 327–350.
[23] Money, A.G., Lines, L., Fernando, S., and Elliman,
A.D. e-Government online forms: design guidelines for
older adults in Europe. Universal Access in the Information
Society 10, 1 (2011), 1–16.
[24] Page, S.E. Diversity and Complexity. Princeton
University Press, New Jersey, 2011.
[25] Papadomichelaki, X. and Mentzas, G. e-GovQual: A
multiple-item scale for assessing e-government service
quality. Government Information Quarterly 29, 1 (2012),
98–109.
[26] Rowe, L.A. and Shoens, K.A. A Form Application
Development System. Proceedings of the 1982 ACM
SIGMOD International Conference on Management of
Data, Orlando, (1982), 28–38.
[27] Shu, N.C., Lum, V.Y., Tung, F.C., and Chang, C.L.
Specification of Forms Processing and Business Procedures
for Office Automation. IEEE Transactions on Software
Engineering SE-8, 5 (1982), 499–512.
[28] Sourouni, A.-M., Lampathaki, F., Mouzakitis, S.,
Charalabidis, Y., and Askounis, D. Paving the Way to
eGovernment Transformation: Interoperability Registry
Infrastructure Development. Proceedings of the 7th
International Conference on Electronic Government, Turin,
(2008), 340–351.
[29] Spivak, S.M. and Brenner, F.C. Standardization
Essentials: Principles and Practice. Marcel Dekker, New
York, 2001.
[30] Tsichritzis, D. Form Management. Communications of
the ACM 25, 7 (1982), 453–478.
[31] van der Aalst, W.M.P., Weske, M., and Grünbauer, D.
Case handling: a new paradigm for business process
support. Data & Knowledge Engineering 53, 2 (2005),
129–162.
[32] Winckler, M., Gaits, V., Vo, D.-B., Firmenich, S., and
Rossi, G. An approach and tool support for assisting users
to fill-in web forms with personal information. Proceedings
of the 29th ACM international conference on Design of
communication, Pisa, (2011), 195–202.
[33] Wroblewski, L. Web Form Design: Filling in the
Blanks. Rosenfeld Media, Brooklyn, New York, 2008.
[34] Wu, J.-H., Doong, H.-S., Lee, C.-C., Hsia, T.-C., and
Liang, T.-P. A methodology for designing form-based
decision support systems. Decision Support Systems 36, 3
(2004), 313–335.
[35] Wu, J.-H. A visual approach to end user form
management. Journal of Computer Information Systems 41,
1 (2000), 31–39.
[36] Yao, S.B., Hevner, A.R., Shi, Z., and Luo, D.
FORMANAGER: An Office Forms Management System.
ACM Transactions on Office Information Systems 2, 3
(1984), 235–262.
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